This textbook explores the different aspects of data mining from the fundamentals to the
complex data types and their applications, capturing the wide diversity of problem domains …

Outlier detection has attracted substantial attention in many applications and research
areas; some of the most prominent applications are network intrusion detection or credit card …

In this research, we propose a novel approach for a multinomial logit model selection
procedure: specifically, we apply association rules analysis to identifying potential …

Local pattern mining algorithms generate sets of patterns, which are typically not directly
useful and have to be further processed before actual application or interpretation. Rather …

This mini-review describes the evolution of different algorithms dedicated to the automated
discovery of chemical fragments associated to (eco) toxicological endpoints. These …

Pattern discovery is at the core of numerous data mining tasks. Although many methods
focus on efficiency in pattern mining, they still suffer from the problem of choosing a …

In this paper we present LeGo, a generic framework that utilizes existing local pattern mining
techniques for global modeling in a variety of diverse data mining tasks. In the spirit of well …

As a side effect of the digitalization of unprecedented amount of data, traditional retrieval
tools proved to be unable to extract hidden and valuable knowledge. Data Mining, with a …

The aim of this paper is to model and mine patterns combining several local patterns (n-ary
patterns). First, the user expresses his/her query under constraints involving n-ary patterns …

Multidimensional databases have been designed to provide decision makers with the
necessary tools to help them understand their data. This framework is different from …